Triple

T10367816
Position Surface form Disambiguated ID Type / Status
Subject Human Traffic E244299 entity
Predicate stars P1956 FINISHED
Object Danny Dyer E866501 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Danny Dyer | Statement: [Human Traffic, stars, Danny Dyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danny Dyer
Context triple: [Human Traffic, stars, Danny Dyer]
  • A. Danny Dyer chosen
    Danny Dyer is an English actor and television personality best known for his tough-guy roles in British films and the soap opera EastEnders.
  • B. Ian Anthony Dale
    Ian Anthony Dale is an American actor best known for his roles in television series such as Hawaii Five-0, The Event, and Salvation.
  • C. Pete Glenister
    Pete Glenister is a British songwriter, guitarist, and producer known for his work with artists such as Alison Moyet and Kirsty MacColl.
  • D. Douglas Hodge
    Douglas Hodge is an English actor and director known for his acclaimed work on stage and screen, including prominent roles in both classical theatre and television comedies.
  • E. Bradley Walsh
    Bradley Walsh is an English actor, comedian, television presenter, and former professional footballer best known for hosting the quiz show "The Chase" and starring in series such as "Law & Order: UK" and "Doctor Who."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e97106448190a075948e63184f47 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d90d76fd88819086c61c40216a8932 completed April 10, 2026, 2:47 p.m.
Created at: April 6, 2026, noon